Image sequence segmentation via heuristic texture analysis and region tracking

Yih H. Jan*, David W. Lin

*Corresponding author for this work

Research output: Contribution to journalConference article

1 Scopus citations


We develop a method for automatic segmentation of natural video sequences. The method is based on low-level spatial and temporal analyses. It features three designs to help facilitate good region segmentation while keeping the computational complexity at a reasonable level. Firstly, a preliminary seed-area identification and a final re-segmentation process are performed on each video frame to help region tracking. Secondly, a simple way to measure homogeneity of texture in a region is devised and the segmentation tries to locate object boundaries at where the texture shows significant changes. And thirdly, a reduced-complexity motion estimation technique is used, so that dense motion fields can be computed at a reasonable complexity. The overall method is organized into four tasks, namely, seed-area identification (for each frame), initial segmentation (only for the first frame in the sequence), motion-based segmentation (for all later frames), and region tracking and updating (also for all later frames). Some examples are provided to illustrate the performance of this method.

Original languageEnglish
Pages (from-to)543-551
Number of pages9
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume4671 II
StatePublished - 1 Jan 2002
EventViual Communications and Image Processing 2002 - San Jose, CA, United States
Duration: 21 Jan 200223 Jan 2002


  • Image sequence segmentation
  • Object tracking

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